• What is a tree?
• How is a tree built?
• What are phylogenetic data?

• Determine the timing of trait evolution

Skink tree from Wright et al. 2015

• Tell homology from convergence

Dolphin, Alex Vasenin via WikiMedia

• Trace the origins of structures

Ask a Biologist illustration of homology

• Taxonomy

• Hennig, 1950 Grundzüge einer Theorie der Phylogenetischen Systematik

  • Taxonomy should be logically consistent with the tree for the group

• Taxonomy

• Hennig, 1950 Grundzüge einer Theorie der Phylogenetischen Systematik

  • Taxonomy should be logically consistent with the tree for the group

• Sneath & Sokal, 1963, 1973

  • Using distance matrices to cluster based on phenetic similarity

library(phytools)

## Loading required package: ape

## Loading required package: maps

tree <- pbtree(n = 5)
plot(tree, cex = 3.5, no.margin = TRUE, edge.width = 1.5)

Tip: What we are putting on the tree. May be species, individuals, or higher-order taxa. May be called terminal node, leaf, one degree node.

plot(tree, cex = 3.5, no.margin = TRUE, edge.width = 1.5)

tree$tip.label

## [1] "t1" "t2" "t3" "t4" "t5"

[1] "t4" "t5" "t1" "t2" "t3"

Access in R: tree$tip.label

plot(tree, cex = 3.5, no.margin = TRUE, edge.width = 1.5)
nodelabels(cex=4)

Node: Where nodes meet, implying a most recent common ancestor. May be called vertex, or three-degree node.

library(ape)
tree$Nnode

## [1] 4

[1] 4

getMRCA(tree, c("t1", "t2"))

## [1] 7

[1] 6

#plot(tree, cex = 3.5, no.margin = TRUE, edge.width = 1.5)
tree$edge

     [,1] [,2]
[1,]    6    7
[2,]    7    8
[3,]    8    1
[4,]    8    2
[5,]    7    3
[6,]    6    9
[7,]    9    4
[8,]    9    5

Branch: What connects the tip to the tree. Can have a variety of units, which we will discuss over the next few days. May be called edge. Access in R: tree$edge

library(phytools)
plotBranchbyTrait(tree,tree$edge.length,method="tips")

tree$edge.length

## [1] 0.5278737 1.6911524 0.5825788 1.1085736 1.1085736 1.5212527 0.6977734
## [8] 0.6977734

[1] 0.01070042 1.00622147 0.36177554 0.36177554 1.36799701 0.23368315
[7] 1.14501427 1.14501427

plot(tree, cex = 3.5, no.margin = TRUE, edge.width = 1.5, direction = "downwards")

plot(tree, cex = 3.5, no.margin = TRUE, edge.width = 1.5, type="fan")

plot(tree, cex = 3.5, no.margin = TRUE, edge.width = 1.5)
nodelabels(cex = 3.5)

rotateNodes(tree, c(7, 8))

## 
## Phylogenetic tree with 5 tips and 4 internal nodes.
## 
## Tip labels:
## [1] "t3" "t2" "t1" "t4" "t5"
## 
## Rooted; includes branch lengths.

Phylogenetic tree with 5 tips and 4 internal nodes.

Tip labels:
[1] "t1" "t5" "t4" "t2" "t3"

Rooted; includes branch lengths.

plot(tree, cex = 3.5, no.margin = TRUE, edge.width = 1.5)

is.monophyletic(tree, c("t1", "t2"), plot = TRUE, edge.width = 1.5, cex = 3.5, no.margin = TRUE)

## [1] FALSE

[1] FALSE

# reroot(tree, node.number)
plot(tree, cex = 3.5, no.margin = TRUE, edge.width = 1.5)

Ingroup: Taxa of interest

Outgroup: Taxon closely related used to root the tree

unroot_tree <- unroot(tree)
plot(unroot_tree, cex = 3.5, no.margin = TRUE, edge.width = 1.5)

• Many ways. We will focus on three:
  • Maximum parsimony
  • Maximum likelihood
  • Bayesian inference

library(alignfigR)

## Welcome to alignfigR!

char_data <- read_alignment("../../data/bears_fasta.fa")
char_data[1:3]

## $Agriarctos_spp
##  [1] "?" "0" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "0"
## [18] "0" "0" "1" "1" "1" "1" "0" "0" "1" "?" "1" "1" "?" "0" "1" "1" "1"
## [35] "1" "0" "1" "1" "0" "?" "?" "0" "1" "1" "1" "0" "?" "?" "?" "?" "?"
## [52] "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?"
## 
## $Ailurarctos_lufengensis
##  [1] "?" "0" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?"
## [18] "0" "0" "1" "1" "1" "1" "0" "1" "1" "?" "1" "1" "?" "0" "?" "?" "?"
## [35] "?" "0" "1" "1" "1" "?" "0" "0" "1" "1" "1" "0" "1" "0" "1" "1" "0"
## [52] "1" "1" "?" "?" "?" "?" "?" "?" "?" "?" "?"
## 
## $Ailuropoda_melanoleuca
##  [1] "1" "0" "1" "1" "1" "1" "0" "1" "1" "0" "1" "0" "0" "1" "0" "0" "0"
## [18] "0" "0" "1" "1" "1" "1" "0" "1" "0" "1" "1" "1" "0" "0" "1" "0" "1"
## [35] "0" "0" "1" "1" "0" "0" "0" "0" "1" "1" "1" "0" "1" "0" "0" "1" "0"
## [52] "1" "1" "0" "0" "0" "1" "0" "0" "0" "1" "0"

$Agriarctos_spp
 [1] "?" "0" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "0"
[18] "0" "0" "1" "1" "1" "1" "0" "0" "1" "?" "1" "1" "?" "0" "1" "1" "1"
[35] "1" "0" "1" "1" "0" "?" "?" "0" "1" "1" "1" "0" "?" "?" "?" "?" "?"
[52] "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?"

$Ailurarctos_lufengensis
 [1] "?" "0" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?"
[18] "0" "0" "1" "1" "1" "1" "0" "1" "1" "?" "1" "1" "?" "0" "?" "?" "?"
[35] "?" "0" "1" "1" "1" "?" "0" "0" "1" "1" "1" "0" "1" "0" "1" "1" "0"
[52] "1" "1" "?" "?" "?" "?" "?" "?" "?" "?" "?"

$Ailuropoda_melanoleuca
 [1] "1" "0" "1" "1" "1" "1" "0" "1" "1" "0" "1" "0" "0" "1" "0" "0" "0"
[18] "0" "0" "1" "1" "1" "1" "0" "1" "0" "1" "1" "1" "0" "0" "1" "0" "1"
[35] "0" "0" "1" "1" "0" "0" "0" "0" "1" "1" "1" "0" "1" "0" "0" "1" "0"
[52] "1" "1" "0" "0" "0" "1" "0" "0" "0" "1" "0"

library(alignfigR)
char_data <- read_alignment("../../data/bears_fasta.fa")
char_data[1:3]

## $Agriarctos_spp
##  [1] "?" "0" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "0"
## [18] "0" "0" "1" "1" "1" "1" "0" "0" "1" "?" "1" "1" "?" "0" "1" "1" "1"
## [35] "1" "0" "1" "1" "0" "?" "?" "0" "1" "1" "1" "0" "?" "?" "?" "?" "?"
## [52] "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?"
## 
## $Ailurarctos_lufengensis
##  [1] "?" "0" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?"
## [18] "0" "0" "1" "1" "1" "1" "0" "1" "1" "?" "1" "1" "?" "0" "?" "?" "?"
## [35] "?" "0" "1" "1" "1" "?" "0" "0" "1" "1" "1" "0" "1" "0" "1" "1" "0"
## [52] "1" "1" "?" "?" "?" "?" "?" "?" "?" "?" "?"
## 
## $Ailuropoda_melanoleuca
##  [1] "1" "0" "1" "1" "1" "1" "0" "1" "1" "0" "1" "0" "0" "1" "0" "0" "0"
## [18] "0" "0" "1" "1" "1" "1" "0" "1" "0" "1" "1" "1" "0" "0" "1" "0" "1"
## [35] "0" "0" "1" "1" "0" "0" "0" "0" "1" "1" "1" "0" "1" "0" "0" "1" "0"
## [52] "1" "1" "0" "0" "0" "1" "0" "0" "0" "1" "0"

$Agriarctos_spp
 [1] "?" "0" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "0"
[18] "0" "0" "1" "1" "1" "1" "0" "0" "1" "?" "1" "1" "?" "0" "1" "1" "1"
[35] "1" "0" "1" "1" "0" "?" "?" "0" "1" "1" "1" "0" "?" "?" "?" "?" "?"
[52] "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?"

$Ailurarctos_lufengensis
 [1] "?" "0" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?"
[18] "0" "0" "1" "1" "1" "1" "0" "1" "1" "?" "1" "1" "?" "0" "?" "?" "?"
[35] "?" "0" "1" "1" "1" "?" "0" "0" "1" "1" "1" "0" "1" "0" "1" "1" "0"
[52] "1" "1" "?" "?" "?" "?" "?" "?" "?" "?" "?"

$Ailuropoda_melanoleuca
 [1] "1" "0" "1" "1" "1" "1" "0" "1" "1" "0" "1" "0" "0" "1" "0" "0" "0"
[18] "0" "0" "1" "1" "1" "1" "0" "1" "0" "1" "1" "1" "0" "0" "1" "0" "1"
[35] "0" "0" "1" "1" "0" "0" "0" "0" "1" "1" "1" "0" "1" "0" "0" "1" "0"
[52] "1" "1" "0" "0" "0" "1" "0" "0" "0" "1" "0"

These data are binary

library(alignfigR)
char_data <- read_alignment("../../data/bears_fasta.fa")
char_data[1:3]

## $Agriarctos_spp
##  [1] "?" "0" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "0"
## [18] "0" "0" "1" "1" "1" "1" "0" "0" "1" "?" "1" "1" "?" "0" "1" "1" "1"
## [35] "1" "0" "1" "1" "0" "?" "?" "0" "1" "1" "1" "0" "?" "?" "?" "?" "?"
## [52] "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?"
## 
## $Ailurarctos_lufengensis
##  [1] "?" "0" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?"
## [18] "0" "0" "1" "1" "1" "1" "0" "1" "1" "?" "1" "1" "?" "0" "?" "?" "?"
## [35] "?" "0" "1" "1" "1" "?" "0" "0" "1" "1" "1" "0" "1" "0" "1" "1" "0"
## [52] "1" "1" "?" "?" "?" "?" "?" "?" "?" "?" "?"
## 
## $Ailuropoda_melanoleuca
##  [1] "1" "0" "1" "1" "1" "1" "0" "1" "1" "0" "1" "0" "0" "1" "0" "0" "0"
## [18] "0" "0" "1" "1" "1" "1" "0" "1" "0" "1" "1" "1" "0" "0" "1" "0" "1"
## [35] "0" "0" "1" "1" "0" "0" "0" "0" "1" "1" "1" "0" "1" "0" "0" "1" "0"
## [52] "1" "1" "0" "0" "0" "1" "0" "0" "0" "1" "0"

$Agriarctos_spp
 [1] "?" "0" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "0"
[18] "0" "0" "1" "1" "1" "1" "0" "0" "1" "?" "1" "1" "?" "0" "1" "1" "1"
[35] "1" "0" "1" "1" "0" "?" "?" "0" "1" "1" "1" "0" "?" "?" "?" "?" "?"
[52] "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?"

$Ailurarctos_lufengensis
 [1] "?" "0" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?" "?"
[18] "0" "0" "1" "1" "1" "1" "0" "1" "1" "?" "1" "1" "?" "0" "?" "?" "?"
[35] "?" "0" "1" "1" "1" "?" "0" "0" "1" "1" "1" "0" "1" "0" "1" "1" "0"
[52] "1" "1" "?" "?" "?" "?" "?" "?" "?" "?" "?"

$Ailuropoda_melanoleuca
 [1] "1" "0" "1" "1" "1" "1" "0" "1" "1" "0" "1" "0" "0" "1" "0" "0" "0"
[18] "0" "0" "1" "1" "1" "1" "0" "1" "0" "1" "1" "1" "0" "0" "1" "0" "1"
[35] "0" "0" "1" "1" "0" "0" "0" "0" "1" "1" "1" "0" "1" "0" "0" "1" "0"
[52] "1" "1" "0" "0" "0" "1" "0" "0" "0" "1" "0"

Always arranged with rows being taxa and columns corresponding to a character - “matrix” structure

Text editor - phylo data, metadata

DNA data tends to be simple

Example character from Brady:

1. Worker, queen, and male. Specialized, stout setae on anterior margin of clypeus: (0) absent; (1) present. The presence of these specialized setae is a putative synapomorphy of Amblyoponinae (Ward, 1994), including Amblyopone and Onychomyrmex.

image via Ask a Biologist

• How do we know we have a truly discrete state?

How do we know we’ve captured the relevant character axes?

image via Ask a biologist, Mike Hagelberg

library(ggplot2)
colors <- c("blue", "purple","white")
plot_alignment(char_data, colors, taxon_labels = TRUE) + theme(text = element_text(size=40))

library(ggplot2)
colors <- c("blue", "purple","white")
plot_alignment(char_data, colors, taxon_labels = TRUE) + theme(text = element_text(size=40))

How do we go from this to a tree?

• Not only applied in phylogenetics
• The simplest explanation for the observed data is the best

• Maximum parsimony: the tree that minimizes the number of “steps”, or changes, on a tree is to be preferred
• Let’s turn to the board for a minute: Parsimony informative, invariant, and parsimony non-informative variation

??? Have them start installs on the next page while we do this.

RStudio –or–Shiny

library(treesiftr)

## Registered S3 method overwritten by 'treeio':
##   method     from
##   root.phylo ape

## 
## Attaching package: 'treesiftr'

## The following object is masked _by_ '.GlobalEnv':
## 
##     tree

aln_path <- "../../data/bears_fasta.fa"
bears <- read_alignment(aln_path)
bear_tree <- multi2di(read.tree("../../data/starting_tree.tre"))
sample_df <- generate_sliding(bears, start_char = 1, stop_char = 5, steps = 1)
print(sample_df)

##   starting_val stop_val step_val
## 1            1        2        1
## 2            2        3        1
## 3            3        4        1
## 4            4        5        1
## 5            5        6        1

  starting_val stop_val step_val
1            1        2        1
2            2        3        1
3            3        4        1
4            4        5        1
5            5        6        1

library(phangorn)
library(ggtree)

## ggtree v1.16.3  For help: https://yulab-smu.github.io/treedata-book/
## 
## If you use ggtree in published research, please cite the most appropriate paper(s):
## 
## - Guangchuang Yu, Tommy Tsan-Yuk Lam, Huachen Zhu, Yi Guan. Two methods for mapping and visualizing associated data on phylogeny using ggtree. Molecular Biology and Evolution 2018, accepted. doi: 10.1093/molbev/msy194- Guangchuang Yu, David Smith, Huachen Zhu, Yi Guan, Tommy Tsan-Yuk Lam. ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods in Ecology and Evolution 2017, 8(1):28-36, doi:10.1111/2041-210X.12628

## 
## Attaching package: 'ggtree'

## The following object is masked from 'package:phytools':
## 
##     read.newick

## The following object is masked from 'package:ape':
## 
##     rotate

output_vector <- generate_tree_vis(sample_df = sample_df,                                        alignment = aln_path, 
                                   tree = bear_tree, 
                                   phy_mat = bears,                                              pscore = TRUE)

## Generating tree for charset:12

## Final p-score 2 after  0 nni operations

## Generating tree for charset:23

## Final p-score 2 after  0 nni operations

## Generating tree for charset:34

## Final p-score 2 after  0 nni operations

## Generating tree for charset:45

## Final p-score 2 after  0 nni operations

## Generating tree for charset:56

## Final p-score 2 after  0 nni operations

output_vector #sample output - you will get more than this when you run in your console

## [[1]]
## NULL
## 
## [[2]]
## NULL
## 
## [[3]]
## NULL
## 
## [[4]]
## NULL
## 
## [[5]]

Parsimony Trees

This is one character. Imagine many - enumeration is not possible.Also note that several trees have the same “best” tree

Image via Mark Holder

• We’re going to take an exercise break and play with PAUP
  • http://phylosolutions.com/paup-test/
  • Download the command line executeable for your OS
  • Copy it into this repository
  • Open a terminal

execute data/bears_morphology.nex

• NOTE: PAUP allows tab-completion
• Open the bears_morphology file in a text editor. Now:

cstatus
tstatus
showmatrix
showdist
log file="mylogfile"

• Try each of these - what information do they give you?

alltrees

What happened here?

Parsimony Trees

Heuristic - use of shortcuts to reduce the number of trees we need to search

hsearch

• What is the name of the heuristic that was used?
• How was the initial tree discovered?
• How many trees were searched?
• How many “best” trees were there, and what is their score?

Heuristic - use of shortcuts to reduce the number of trees we need to search

hsearch swap = nni

• How many trees were examined with this algorithm? Why is this number so much smaller?
• How many “best” trees were found, and what is their score?

Heuristic - use of shortcuts to reduce the number of trees we need to search

hsearch swap = spr

• How many trees were examined with this algorithm?
• How many “best” trees were found, and what is their score?
• When would we expect searching algorithm to matter strongly?

savetrees from=1 to=1 file=results/tree1.tre;
savetrees from=2 to=2 file=results/tree2.tre;
savetrees from=3 to=3 file=results/tree3.tre;